Turbomachines are widely utilized in fields such as power generation and aircraft engines. For example, a conventional gas turbine system includes a compressor section, a combustor section, and at least one turbine section. The compressor section is configured to compress air as the air flows through the compressor section. The air is then flowed from the compressor section to the combustor section, where it is mixed with fuel and combusted, generating a hot gas flow. The hot gas flow is provided to the turbine section, which utilizes the hot gas flow by extracting energy from it to power the compressor, an electrical generator, and other various loads.
During operation of a turbomachine, various components (collectively known as turbine components) within the turbomachine and particularly within the turbine section of the turbomachine, such as turbine blades, may be subject to creep due to high temperatures and stresses. For turbine blades, creep may cause portions of or the entire blade to elongate so that the blade tips contact a stationary structure, for example a turbine casing, and potentially cause unwanted vibrations and/or reduced performance during operation.
Accordingly, it is desirable to monitor turbine components for creep. One approach to monitoring turbine components for creep is to configure strain sensors on the components, and analyze the strain sensors at various intervals to monitor for deformations associated with creep strain. However, such deformation can in many cases be on the order of 0.01% of an original dimension, thus requiring specialized equipment for strain monitoring.
One approach to monitoring such strain sensors is to obtain two-dimensional images of the strain sensors, and compare the dimensions of the strain sensors in images taken at varying times for an associated turbine component. Typically, dimensions along two axes, such as length and width dimension along X- and Y-axes, can be directly measured in such images. However, dimensions along a third axis, such as a height or thickness dimension along a Z-axis, cannot be directly measured in such images. Rather, dimensions along this third axis are inferred through the contrast shown in the images. For example, digital image correlation may use two-dimensional images to assemble a three-dimensional profile. Contrast in the various images is utilized to obtain dimensions along a third axis in order to assemble the three-dimensional profile.
These approaches to measuring the third axes can lead to inaccuracies in resulting measurements. For example, if the device utilized to obtain the two-dimensional images is not identically positioned relative to a strain sensor for each image to be compared, unintended changes in contrast can result, leading to measurement inaccuracies.
Accordingly, alternative systems and methods for monitoring turbine component strain are desired in the art. In particular, system and methods which provide improved, accurate measurements in three dimensions would be advantageous.